htmltools::tagList(rmarkdown::html_dependency_font_awesome())
# Render the R Markdown document
rmarkdown::render("portfolio.Rmd", output_file = "../portfolio.html")
Check out some examples of our visualizations
Drivers are more likely to be involved in a traffic fatality at specific hours during the day, namely late at night.
Explanation:This graph supports our alternative hypothesis, and shows that early morning also is a high traffic fatality time. The speeding information is not relevant for this specific hypothesis.
Hypothesis 2:There is no relationship between running a red light or not and the number of fatalities in the accident.
Alternate hypothesis:Accidents where a red light was run are more likely to have higher fatality counts.
Explanation:Our data seems to refute the alternate hypothesis we made, as well as our null hypothesis. Accidents where a red light was not run had higher fatality counts.
The likelihood of fatality as a result of drivers who were speeding is equal to the likelihood of fatality as a result of drivers who did not speed.
Alternate hypothesis:The likelihood of fatality as a result of drivers who were speeding is greater than the likelihood of fatality as a result of drivers who did not speed.
Explanation:There is not much difference and a lot of overlap with error bars between speeding and non-speeding traffic fatality occurrences. This looks in favor of the null, but we should check with more variables to see if speeding interacts with any of them.